V.A. Yemelyanov1, D.A. Petrosov2, N.Yu. Yemelyanova3, D.V. Chistov4

1-4 Financial University under the Government of the Russian Federation (Moscow, Russia)

The article is devoted to the development of a new automated system for monitoring the state of the ladle cars. The authors propose a neural network approach to support decision-making on the operation mode of the ladle cars, which differs from the existing neural network assessment of the factors affecting the possibility of their use, which makes it possible to automate the operation of determining the operation mode of the ladle cars. In the course of the study, a neural network was synthesized to determine the operating mode of the ladle cars.

As a result, the authors have developed client-server software that implements the information technology methods proposed by the authors for monitoring the technical condition and decision support during the operation of ladle cars. The developed software implements the proposed neural network approach to determining the operating mode of the ladle cars.

Yemelyanov V.A., Petrosov D.A., Yemelyanova N.Yu., Chistov D.V. Automation of the monitoring the technical condition of ladle cars on the basis of artificial neural networks. Neurocomputers. 2022. V. 24. № 5. Р. 36-43. DOI: https://doi.org/10.18127/j19998554-202205-04 (in Russian)

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